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Description

After eight months of persistent cloud cover, coastal Virginia finally had a week of clear nights in September and I was imaging for most of them. The Pacman Nebula was my main target and I became determined to push 10 hours of total exposure on this target. Since most of these nights were during the workweek,I was a tired mess by the time clouds returned so I had no idea how much I actually collected until weeks later. I met my target and accumulated over 14 hours of subframes, though I ultimately tossed about 2 hours due to passing clouds and contrast degradation as the nebula slipped below 30 degrees altitude into the light dome to the west.

My choice of sub exposure duration (500 s) was an experiment to see what happens when the histogram background peak lies around 40% rather than 33% as is commonly recommended (i.e, sort of an “expose to the right” methodology). Plus, this was the first time I used an IDAS-D1 light pollution filter which necessitated longer exposures. That filter, by the way, worked exceptionally well at increasing contrast with the subject given my light pollution environment. It is a keeper. Anyhow, even though these longer sub exposures ensured the nebula signal was adequately sampled, the consequence was that several brighter stars were saturated so I worked in post processing to shove color back into the cores. I had intended to revisit this target with shorter exposures to better capture the stars, but the moon, clouds and enticement of other targets has led my attention elsewhere until next year. My conclusion from this experiment? I will probably lower my sub exposure time at my suburban imaging location.

The integrated image had quite nice SNR, comparable to what I have seen from 2 hours of integration time at a dark site. Let’s put that into perspective: 12 hours in suburbia versus 2 hours in the boonies. Argh, where is my free lunch?

In linear post processing, I followed David Ault’s excellent M42 tutorial for deconvolution and noise reduction (link below). His tips on mask generation for those processes contribute immensely to their success. This was also the first time I achieved good results with deconvolution which always made a mess of things in the past. For this image, it sharpen everything subtly which trickled to downstream processes without ill effect. Also, David’s linear noise reduction techniques worked marvelously. Usually, I struggled with noise reduction in the linear stage and pushed it off to ACDNR after non-linear steps. Here, it reduced noise effectively and I did not bother with any further noise reduction down the line.

I really didn’t push the processing too hard with this one with LocalHistogramEqualization or HDRMultiscaleTranform like I would like to have. Even though the integrated image had good SNR at the onset, once I subtracted away the light polluted background, the object SNR was on shaky ground. So, I just stuck to a basic histogram stretch and then micro-contrast curves to accentuate details in the nebula. I tried to not push the color saturation of the nebula too hard either, otherwise it would become monochrome red when in reality there is a bit of blue-green hues towards the middle due to OIII emission. I’ll need to add some OIII data to pull that out of this data. Another struggle was the mess of stars in this field of view which I shrunk slightly. I didn’t want to shrink them too far since most of the color was in the star halos and the cores are saturated. I think I struck a good balance.

Altogether, I am satisfied with the final image. It was worth the late nights and grumpy trips to Starbucks the following mornings.

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